Shifting ranges and conservation challenges for lemurs in the face of climate change

Geospatial modeling is one of the most powerful tools available to conservation biologists for estimating current species ranges of Earth's biodiversity. Now, with the advantage of predictive climate models, these methods can be deployed for understanding future impacts on threatened biota. Here, we employ predictive modeling under a conservative estimate of future climate change to examine impacts on the future abundance and geographic distributions of Malagasy lemurs. Using distribution data from the primary literature, we employed ensemble species distribution models and geospatial analyses to predict future changes in species distributions. Current species distribution models (SDMs) were created within the BIOMOD2 framework that capitalizes on ten widely used modeling techniques. Future and current SDMs were then subtracted from each other, and areas of contraction, expansion, and stability were calculated. Model overprediction is a common issue associated Malagasy taxa. Accordingly, we introduce novel methods for incorporating biological data on dispersal potential to better inform the selection of pseudo‐absence points. This study predicts that 60% of the 57 species examined will experience a considerable range of reductions in the next seventy years entirely due to future climate change. Of these species, range sizes are predicted to decrease by an average of 59.6%. Nine lemur species (16%) are predicted to expand their ranges, and 13 species (22.8%) distribution sizes were predicted to be stable through time. Species ranges will experience severe shifts, typically contractions, and for the majority of lemur species, geographic distributions will be considerably altered. We identify three areas in dire need of protection, concluding that strategically managed forest corridors must be a key component of lemur and other biodiversity conservation strategies. This recommendation is all the more urgent given that the results presented here do not take into account patterns of ongoing habitat destruction relating to human activities.     

Scale effects in species distribution models: implications for conservation planning under climate change

Predictions of future species' ranges under climate change are needed for conservation planning, for which species distribution models (SDMs) are widely used. However, global climate model-based (GCM) output grids can bias the area identified as suitable when these are used as SDM predictor variables, because GCM outputs, typically at least 50x50 km, are biologically coarse. We tested the assumption that species ranges can be equally well portrayed in SDMs operating on base data of different grid sizes by comparing SDM performance statistics and area selected by four SDMs run at seven grid sizes, for nine species of contrasting range size. Area selected was disproportionately larger for SDMs run on larger grid sizes, indicating a cut-off point above which model results were less reliable. Up to 2.89 times more species range area was selected by SDMs operating on grids above 50x50 km, compared to SDMs operating at 1 km2. Spatial congruence between areas selected as range also diverged as grid size increased, particularly for species with ranges between 20000 and 90000 km2. These results indicate the need for caution when using such data to plan future protected areas, because an overly large predicted range could lead to inappropriate reserve location selection.     

Projected changes in distributions of Australian tropical savanna birds under climate change using three dispersal scenarios

Identifying the species most vulnerable to extinction as a result of climate change is a necessary first step in mitigating biodiversity decline. Species distribution modeling (SDM) is a commonly used tool to assess potential climate change impacts on distributions of species. We use SDMs to predict geographic ranges for 243 birds of Australian tropical savannas, and to project changes in species richness and ranges under a future climate scenario between 1990 and 2080. Realistic predictions require recognition of the variability in species capacity to track climatically suitable environments. Here we assess the effect of dispersal on model results by using three approaches: full dispersal, no dispersal and a partial-dispersal scenario permitting species to track climate change at a rate of 30 km per decade. As expected, the projected distributions and richness patterns are highly sensitive to the dispersal scenario. Projected future range sizes decreased for 66% of species if full dispersal was assumed, but for 89% of species when no dispersal was assumed. However, realistic future predictions should not assume a single dispersal scenario for all species and as such, we assigned each species to the most appropriate dispersal category based on individual mobility and habitat specificity; this permitted the best estimates of where species will be in the future. Under this "realistic" dispersal scenario, projected ranges sizes decreased for 67% of species but showed that migratory and tropical-endemic birds are predicted to benefit from climate change with increasing distributional area. Richness hotspots of tropical savanna birds are expected to move, increasing in southern savannas and southward along the east coast of Australia, but decreasing in the arid zone. Understanding the complexity of effects of climate change on species' range sizes by incorporating dispersal capacities is a crucial step toward developing adaptation policies for the conservation of vulnerable species.     

A framework integrating physiology,dispersal and land‐use to project species ranges under climate change

To study the potential effects of climate change on species, one of the most popular approaches are species distribution models (SDMs). However, they usually fail to consider important species‐specific biological traits, such as species’ physiological capacities or dispersal ability. Furthermore, there is consensus that climate change does not influence species distributions in isolation, but together with other anthropogenic impacts such as land‐use change, even though studies investigating the relative impacts of different threats on species and their geographic ranges are still rare. Here we propose a novel integrative approach which produces refined future range projections by combining SDMs based on distribution, climate, and physiological tolerance data with empirical data on dispersal ability as well as current and future land‐use. Range projections based on different combinations of these factors show strong variation in projected range size for our study species Emberiza hortulana. Using climate and physiological data alone, strong range gains are projected. However, when we account for land‐use change and dispersal ability, future range‐gain may even turn into a future range loss. Our study highlights the importance of accounting for biological traits and processes in species distribution models and of considering the additive effects of climate and land‐use change to achieve more reliable range projections. Furthermore, with our approach we present a new tool to assess species’ vulnerability to climate change which can be easily applied to multiple species.     

Beyond species distribution modeling: A landscape genetics approach to investigating range shifts under future climate change

Understanding how biodiversity will respond to future climate change is a major conservation and societal challenge. Climate change is predicted to force many species to shift their ranges in pursuit of suitable conditions. This study aims to use landscape genetics, the study of the effects of environmental heterogeneity on the spatial distribution of genetic variation, as a predictive tool to assess how species will shift their ranges to track climatic changes and inform conservation measures that will facilitate movement. The approach is based on three steps: 1) using species distribution models (SDMs) to predict suitable ranges under future climate change, 2) using the landscape genetics framework to identify landscape variables that impede or facilitate movement, and 3) extrapolating the effect of landscape connectivity on range shifts in response to future climate change. I show how this approach can be implemented using the publicly available genetic dataset of the grey long-eared bat, Plecotus austriacus, in the Iberian Peninsula. Forest cover gradient was the main landscape variable affecting genetic connectivity between colonies. Forest availability is likely to limit future range shifts in response to climate change, primarily over the central plateau, but important range shift pathways have been identified along the eastern and western coasts. I provide outputs that can be directly used by conservation managers and review the viability of the approach. Using landscape genetics as a predictive tool in combination with SDMs enables the identification of potential pathways, whose loss can affect the ability of species to shift their range into future climatically suitable areas, and the appropriate conservation management measures to increase landscape connectivity and facilitate movement.     

Predicting range shifts of Davidia involucrata Ball. under future climate change

Understanding and predicting how species will respond to climate change is crucial for biodiversity conservation. Here, we assessed future climate change impacts on the distribution of a rare and endangered plant species, Davidia involucrate in China, using the most recent global circulation models developed in the sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC6). We assessed the potential range shifts in this species by using an ensemble of species distribution models (SDMs). The ensemble SDMs exhibited high predictive ability and suggested that the temperature annual range, annual mean temperature, and precipitation of the driest month are the most influential predictors in shaping distribution patterns of this species. The projections of the ensemble SDMs also suggested that D. involucrate is very vulnerable to future climate change, with at least one‐third of its suitable range expected to be lost in all future climate change scenarios and will shift to the northward of high‐latitude regions. Similarly, at least one‐fifth of the overlap area of the current nature reserve networks and projected suitable habitat is also expected to be lost. These findings suggest that it is of great importance to ensure that adaptive conservation management strategies are in place to mitigate the impacts of climate change on D. involucrate.     

The impact of climate change on the future distribution of priority crop wild relatives in Indonesia and implications for conservation planning

The analysis of climate change impact is essential to include in conservation planning of crop wild relatives (CWR) to provide the guideline for adequate long-term protection under unpredictable future environmental conditions. These resources play an important role in sustaining the future of food security, but the evidence shows that they are threatened by climate change. The current analyses show that five taxa were predicted to have contraction of more than 30 % of their current ranges: Artocarpus sepicanus (based on RCP 4.5 in both no dispersal and unlimited dispersal scenario and RCP 8.5 in no dispersal scenario by 2050), Ficus oleifolia (RCP 4.5 5 in both no dispersal and unlimited dispersal scenario by 2080), Cocos nucifera and Dioscorea alata (RCP 8.5 in both no dispersal and unlimited dispersal scenario by 2050), and Ficus chartacea (RCP 8.5 in both no dispersal and unlimited dispersal scenario by 2050 and 2080). It shows that the climate change impact is species-specific. Representative Concentration Pathways (RCP) of greenhouse gas (GHG) emission and dispersal scenarios influence the prediction models, and the actual future distribution range of species falls in between those scenarios. Climate refugia, holdout populations, and non-analogue community assemblages were identified based on the Protected Areas (PAs) network. PAs capacity is considered an important element in implementing a conservation strategy for the priority CWR. In areas where PAs are isolated and have less possibility to build corridors to connect each other, such as in Java, unlimited dispersal scenarios are unlikely to be achieved and assisted dispersal is suggested. The holdout populations should be the priority target for the ex situ collection. Therefore, by considering the climate refugia, PAs capacity and holdout populations, the goal of keeping high genetic variations for the long-term conservation of CWR in Indonesia can be achieved.     

The fate of European breeding birds under climate,land‐use and dispersal scenarios

Many species have already shifted their distributions in response to recent climate change. Here, we aimed at predicting the future breeding distributions of European birds under climate, land‐use, and dispersal scenarios. We predicted current and future distributions of 409 species within an ensemble forecast framework using seven species distribution models (SDMs), five climate scenarios and three emission and land‐use scenarios. We then compared results from SDMs using climate‐only variables, habitat‐only variables or both climate and habitat variables. In order to account for a species’ dispersal abilities, we used natal dispersal estimates and developed a probabilistic method that produced a dispersal scenario intermediate between the null and full dispersal scenarios generally considered in such studies. We then compared results from all scenarios in terms of future predicted range changes, range shifts, and variations in species richness. Modeling accuracy was better with climate‐only variables than with habitat‐only variables, and better with both climate and habitat variables. Habitat models predicted smaller range shifts and smaller variations in range size and species richness than climate models. Using both climate and habitat variables, it was predicted that the range of 71% of the species would decrease by 2050, with a 335 km median shift. Predicted variations in species richness showed large decreases in the southern regions of Europe, as well as increases, mainly in Scandinavia and northern Russia. The partial dispersal scenario was significantly different from the full dispersal scenario for 25% of the species, resulting in the local reduction of the future predicted species richness of up to 10%. We concluded that the breeding range of most European birds will decrease in spite of dispersal abilities close to a full dispersal hypothesis, and that given the contrasted predictions obtained when modeling climate change only and land‐use change only, both scenarios must be taken into consideration.     

Genetic landscape and landscape connectivity of Ceratopteris thalictroides,an endangered aquatic fern

Global climate change will have great impacts on ecosystems with high biodiversity and landscape connectivity. Here, we employ species distribution models (SDMs) and geospatial analyses to predict future changes in C. thalictroides distribution under the future climate change based on Community Climate System Model (CCSM4). We predict the ranges of C. thalictroides will contract about 11,523 km² from the present to the year 2080. The changes in species distribution present a main range contraction in high latitude regions. We map the patterns of genetic divergence and diversity using the Genetic Landscape GIS Toolbox in ArcGIS v10.2. By visualizing dispersal networks in SDMtoolbox v 1.1, we predict a major decrease in connectivity will occur between YD (Yingde) and NP (Nanping) population. Populations with high diversity and divergence regions were considered to be evolutionary hotspots. Therefore, we suggest the populations CZ(Chengzhou), YD(Yingde), HP(Hepu), SY(Sanya), DH(Dinghu) and NP(Nanping) are in need of protection, concluding that strategically maintained ecological connectivity must be a key component of conservation strategies for C. thalictroides. We believe the creation of genetic landscape based on genetic datasets and connectivity assessment in relation to climate change will provide increasingly useful information and new implications for prioritizing the conservation of the endangered species.     

Microclimate species distribution models estimate lower levels of climate-related habitat loss for salamanders

Species distribution models (SDMs) largely rely on free-air temperatures at coarse spatial resolutions to predict habitat suitability, potentially overlooking important microhabitat. Integrating microclimate data into SDMs may improve predictions of organismal responses to climate change and support targeting of conservation assets at biologically relevant scales, especially for small, dispersal-limited species vulnerable to climate-change-induced range loss. We integrated microclimate data that account for the buffering effects of forest vegetation into SDMs at a very high spatial resolution (3 m²) for three plethodontid salamander species in Great Smoky Mountains National Park (North Carolina and Tennessee). Microclimate SDMs were used to characterize potential changes to future plethodontid habitat, including habitat suitability and habitat spatial patterns. Additionally, we evaluated spatial discrepancies between predictions of habitat suitability developed with microclimate and coarse-resolution, free-air climate data. Microclimate SDMs indicated substantial losses to plethodontid ranges and highly suitable habitat by mid-century, but at much more conservative levels than coarse-resolution models. Coarse-resolution SDMs generally estimated higher mid-century losses to plethodontid habitat compared to microclimate models and consistently undervalued areas containing highly suitable microhabitat. Furthermore, microclimate SDMs revealed potential areas of future gain in highly suitable habitat within current species’ ranges, which may serve as climatic microrefugia. Taken together, this study highlights the need to develop microclimate SDMs that account for vegetation and its biophysical effects on near-surface temperatures. As microclimate datasets become increasingly available across the world, their integration into correlative and mechanistic SDMs will be imperative for accurately estimating organismal responses to climate change and helping environmental managers tasked with spatially prioritizing conservation assets.     

Forecasting the combined effects of future climate and land use change on the suitable habitat of Davidia involucrata Baill

Accurately predicting the future distribution of species is crucial for understanding how species will response to global environmental change and for evaluating the effectiveness of current protected areas (PAs). Here, we assessed the effect of climate and land use change on the projected suitable habitats of Davidia involucrata Baill under different future scenarios using the following two types of models: (a) only climate covariates (climate SDMs) and (b) climate and land use covariates (full SDMs). We found that full SDMs perform significantly better than climate SDMs in terms of both AUC (p < .001) and TSS (p < .001) and also projected more suitable habitat than climate SDMs both in the whole study area and in its current suitable range, although D. involucrate is predicted to loss at least 26.96% of its suitable area under all future scenarios. Similarly, we found that these range contractions projected by climate SDMs would negate the effectiveness of current PAs to a greater extent relative to full SDMs. These results suggest that although D. involucrate is extremely vulnerability to future climate change, conservation intervention to manage habitat may be an effective option to offset some of the negative effects of a changing climate on D. involucrate and can improve the effectiveness of current PAs. Overall, this study highlights the necessity of integrating climate and land use change to project the future distribution of species.     

A framework for assessing the vulnerability of species to climate change: a case study of the Australian elapid snakes

Frameworks that provide a system for assessing species according to their vulnerability to climate change can offer considerable guidance to conservation managers who need to allocate limited resources among a large number of taxa. To date, climate change vulnerability assessments have largely been based on projected changes in range size derived from the output of species distribution models (SDMs). A criticism of risk assessments based solely on these models is that information on species ecological and life history traits is lacking. Accordingly, we developed a points-based framework for assessing species vulnerability to climate change that considered species traits together with the projections of SDMs. Applying this method to the Australian elapid snakes (family Elapidae), we determined which species may be particularly susceptible in the future and assessed broad-scale biogeographic patterns in species vulnerability. By offering a more comprehensive and rigorous method for assessing vulnerability than those based solely on SDMs, this framework provides greater justification for resource allocation, and can help guide decisions regarding the most appropriate adaptation strategies.     

Evaluating drivers of vulnerability to climate change: a guide for insect conservation strategies

Ongoing global climate change presents serious challenges in conservation biology, forcing us to revisit previous tools and principles based on how species may respond to novel climatic conditions. There is currently a major gap between predictions of species vulnerability and management strategies, despite the fact that linking these areas is fundamental for future biodiversity conservation. Herein, we evaluate what drives vulnerability to climate change in three Iberian endemic water beetles, representing three independent colonizations of the same habitat, employing comparative thermal physiology, species distribution models and estimations of species dispersal capacity. We derive conservation strategies for each species based on their differential capacity to persist and/or potential to shift their ranges in response to global warming. We demonstrate that species may be affected by climatic warming in very different ways, despite having broadly similar ecological and biogeographical traits. The proposed framework provides an effective complement to traditional species vulnerability assessments, and could aid the development of more effective conservation strategies in the face of global warming.     

Dispersal limitation and spatial scale affect model based projections of Pinus uncinata response to climate change in the Pyrenees

Species Distribution Models (SDMs) were employed to assess the potential impact of climate change on the distribution of Pinus uncinata in the Pyrenees, where it is the dominant tree species in subalpine forest and alpine tree lines. Predicting forest response to climate change is a challenging task in mountain regions but also a conservation priority. We examined the potential impact of spatial scale on SDM projections by conducting all analyses at four spatial resolutions. We further examined the potential effect of dispersal constraints by applying a threshold distance of maximal advancement derived from a spatially explicit, individual‐based simulation model of tree line dynamics. Under current conditions, SDMs including climatic factors related to stress or growth limitation performed best. These models were then employed to project P. uncinata distribution under two emission scenarios, using data generated from several regional climate models. At the end of this century, P. uncinata is expected to migrate northward and upward, occupying habitat currently inhabited by alpine plant species. However, consideration of dispersal limitation and/or changing the spatial resolution of the analysis modified the assessment of climate change impact on mountain ecosystems, especially in the case of estimates of colonization and extinction at the regional scale. Our study highlights the need to improve the characterization of biological processes within SDMs, as well as to consider simultaneously different scales when assessing potential habitat loss under future climate conditions.     

物种分布模型的发展及评价方法

物种分布模型已被广泛地应用于以保护区规划、气候变化对物种分布的影响等为目的的研究。回顾了已经得到广泛应用的多种物种分布模型,总结了评价模型性能的方法。基于物种分布模型的发展和应用以及性能评价中尚存在的问题,本文认为:在物种分布模型中集成样本选择模块能够避免模型预测过程中的过度拟合及欠拟合,增加变量选择模块可评估和降低变量之间自相关性的影响,增加生物因子以及将物种对环境的适应性机制(及扩散行为特征)和潜在分布模型进行结合,是提高模型预测性能的可行方案;在模型性能的评价方面,采用赤池信息量可对模型的预测性能进行客观评价。相关建议可为物种分布建模提供参考。     

Choice of baseline climate data impacts projected species' responses to climate change

Climate data created from historic climate observations are integral to most assessments of potential climate change impacts, and frequently comprise the baseline period used to infer species‐climate relationships. They are often also central to downscaling coarse resolution climate simulations from General Circulation Models (GCMs) to project future climate scenarios at ecologically relevant spatial scales. Uncertainty in these baseline data can be large, particularly where weather observations are sparse and climate dynamics are complex (e.g. over mountainous or coastal regions). Yet, importantly, this uncertainty is almost universally overlooked when assessing potential responses of species to climate change. Here, we assessed the importance of historic baseline climate uncertainty for projections of species' responses to future climate change. We built species distribution models (SDMs) for 895 African bird species of conservation concern, using six different climate baselines. We projected these models to two future periods (2040–2069, 2070–2099), using downscaled climate projections, and calculated species turnover and changes in species‐specific climate suitability. We found that the choice of baseline climate data constituted an important source of uncertainty in projections of both species turnover and species‐specific climate suitability, often comparable with, or more important than, uncertainty arising from the choice of GCM. Importantly, the relative contribution of these factors to projection uncertainty varied spatially. Moreover, when projecting SDMs to sites of biodiversity importance (Important Bird and Biodiversity Areas), these uncertainties altered site‐level impacts, which could affect conservation prioritization. Our results highlight that projections of species' responses to climate change are sensitive to uncertainty in the baseline climatology. We recommend that this should be considered routinely in such analyses.     

Dispersal and species’ responses to climate change

Dispersal is fundamental in determining biodiversity responses to rapid climate change, but recently acquired ecological and evolutionary knowledge is seldom accounted for in either predictive methods or conservation planning. We emphasise the accumulating evidence for direct and indirect impacts of climate change on dispersal. Additionally, evolutionary theory predicts increases in dispersal at expanding range margins, and this has been observed in a number of species. This multitude of ecological and evolutionary processes is likely to lead to complex responses of dispersal to climate change. As a result, improvement of models of species’ range changes will require greater realism in the representation of dispersal. Placing dispersal at the heart of our thinking will facilitate development of conservation strategies that are resilient to climate change, including landscape management and assisted colonisation. Synthesis This article seeks synthesis across the fields of dispersal ecology and evolution, species distribution modelling and conservation biology. Increasing effort focuses on understanding how dispersal influences species' responses to climate change. Importantly, though perhaps not broadly widely‐recognised, species' dispersal characteristics are themselves likely to alter during rapid climate change. We compile evidence for direct and indirect influences that climate change may have on dispersal, some ecological and others evolutionary. We emphasise the need for predictive modelling to account for this dispersal realism and highlight the need for conservation to make better use of our existing knowledge related to dispersal.     

The identification and conservation of climate refugia for two Colombian endemic titi (Plecturocebus) monkeys

Natural resource managers face the challenge of developing conservation plans for key species and given that anthropogenic climate change (CC) effects on biodiversity are becoming increasingly evident, the new challenge is to properly incorporate CC adaptation strategies into such plans. Thus, the objective of this study is to evaluate the potential CC effects on the climatically suitable areas for two Colombian endemic titi monkeys Plecturocebus ornatus and P. caquetensis and to identify the prospective climate refugia as macro-ecological adaptation strategies for each species. A detailed ecological niche modeling (ENM) approach was applied with the maximum entropy algorithm, using presence records and different sets of bioclimatic variables describing baseline (1960–1990) and future climates (∼2070). Models of future climatic suitability were generated using projections of variables under a stabilization (RCP4.5) and business as usual (RCP8.5) scenarios with data from two general circulation models (GCMs) describing storylines of increasing (CESM1_CAM5) and decreasing (CSIRO_ACCESS1_3) rainfall patterns. The results for both species indicate that in a warmer future, opposite rainfall patterns and choice of the bioclimatic variables may lead to divergent responses on the extent and geographic distribution of their climatic niche, which varied from regions gaining, losing, and retaining suitability in potential climate refugia. Moreover, CC represents a serious threat for P. caquetensis and P. ornatus since their ranges may be largely exposed to novel climates. Their baseline climatic suitability area is projected to shrink and shift to higher elevations in the Andes mountains, and the climate refugia identified for both species are poorly covered by protected areas. Therefore, the climate refugia identified in this work and the management recommendations offered should be considered by species conservation plans to contribute to the selection of priority regions for conservation actions. The modeling approach reveals the uncertainties arising from the selection of bioclimatic variables and GCMs in ENM, which can be replicated to identify climate refugia targeting different species of conservation concern.     

Subpopulations of Cryptocephalus beetles (Coleoptera: Chrysomelidae): geographically close but genetically far

Abstract. The leaf beetles Cryptocephalus coryli, C. decemmaculatus and C. nitidulus are of conservation concern and are included on the UK Biodiversity Action Plan. The distinctiveness of the disjunct remaining populations of these beetles was compared to that of more continuously distributed Cryptocephalus species. This was carried out with a view to defining evolutionary significant units (ESUs) in the rare species. A portion of the cytochrome b gene, an intergenic spacer and partial tRNA was analysed from 93 specimens of Cryptocephalus beetle (Coleoptera: Chrysomelidae). Considerable sequence divergence was apparent in all the species, even at an intersite scale when the distances between sampled localities were very small (< 1 km). Intrapopulation, intersite and interpopulation divergence observed in the rare species was reflected in the species that have a more continuous distribution, implying that dispersal ability in these species is poor and gene flow can be impeded by relatively trivial barriers to dispersal. The evidence suggests that the disjunct populations of the rare Cryptocephalus species can, tentatively, be considered as ESUs. This has important implications for management strategies and reintroductions.     

Identification of evolutionarily significant units in the Cuban endemic damselfly <Emphasis Type="Italic">Hypolestes trinitatis</Emphasis> (Odonata: Hypolestidae)

Species classification may not reflect the underlying/cryptic genetic diversity which should otherwise be conserved as it represents the potential of populations to evolve and adapt. The identification of evolutionarily significant units (ESUs) allows cryptic genetic diversity to be taken into account when designating conservation priorities. Here, we used mitochondrial and nuclear DNA sequences integrated with ecological niche models (ENM) to identify ESUs in Hypolestes trinitatis, a threatened Cuban endemic damselfly species. We found that this species comprises two distinct genetic groups in Central and Eastern Cuba respectively, which are also geographically isolated, as shown by ENM. Therefore, we propose these groups to be considered as different ESUs. According with their extent of occurrence, number of locations and inferred decline of habitat extent and quality, Central and Eastern ESUs qualify as Endangered [EN B1b(iii)] and Vulnerable [VU B1b(iii)], respectively.